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Automating Utilities Inspection


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How EDP, Portugal’s leading energy provider, leveraged DefinedCrowd’s training data expertise in computer vision to improve infrastructure maintenance procedures.

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Automating Utilities Inspection

  1. 1. Keeping a nation’s lights on means constantly inspecting electricity poles for damage. Before EDP partnered with DefinedCrowd, teams of specialists had to jump into helicopters, survey and photograph poles from way up in the sky and use those photographs to manually fill out damage reports when the day was done. That’s a slow, expensive process with a lot of moving parts to answer a simple question: “which of our poles needs fixing?” The Challenge As a proof-of-concept, we first delivered a model capable of identifying electricity poles and their components (insulators and crossbars. That meant gathering 12,500 images — 7,000 with poles — that were then annotated by our highly-skilled Neevo community (45,000+ strong). We used 3,000 of those images to train a pole detection model and 500 more to test it. Our Solution Next, we built damage detection models by hand-selecting a subset of 900 high-resolution images and sending them out to our Neevo workforce. They identified the type of damage in each, and then we used those annotated images to train and test one model to keep track of damaged or missing insulators and another to detect corrosion on crossbars. Step 1 Pole Detection Step 2 Damage Detection With these models, EDP is on the path to faster, cheaper, and more accurate asset management processes (APM). In the short-term, that means drones will feed high-quality images of poles into automated systems that will deliver comprehensive damage reports as a result. In the long-term, automated APM will allow EDP to ask and answer more sophisticated maintenance questions. The corrective present, “which poles need fixing?” will be replaced by the predictive future, “which of our poles will need fixing?” The Results pole 0.847 pole 0.850 pole 0.846 pole 0.844 missing damaged corrosion Automating Utilities Inspection EDP, CaseStudy images gathered 12,500 pole images w/poles annotated 7,000 0110100111 0110100111 0101010110 1010110100 0101011011 annotated images trained & tested model 3,500 damaged poles w/damages annotated 900 0110100111 0110100111 0101010110 1010110100 0101011011 annotated images trained & tested model 900 F1-score 91% Recall 91% Precision 93% F1-score 81% Recall 87% Precision 75% At EDP, models built on DefinedCrowd’s guaranteed quality training-data mean better answers to better questions. Are you asking the right ones? S E AT T L E L I S B O N P O R T O T O K Y O Follow us Contact us Visit us Corroded Poles damage results Counting Insulators damage results